The principal function of vision is to provide information about the geometrical structure of the environment--about the 3-D shapes, locations, and motions of objects and about the location and motion of the observer. Precise and globally consistent measures of this environmental structure are obtained from changing stimulus patterns distributed both spatially and temporally over two retinal surfaces. This basic visual achievement remains poorly understood, however. A central empirical and theoretical problem is to specify the visually detected geometrical properties that carry information about environmental structure. Analysis of the physiological processes underlying spatial vision depends on an understanding of the specific geometric relationships to which vision is sensitive. The objective of this research project is to identify the geometric relationships in spatially and temporally varying stimulus patterns that permit precise and globally consistent discriminations of spatial structure. The specific aim is to quantify the acuities of human observers in discriminating both local and global spatial relations in changing stimulus patterns. The proposed experiments focus on stimulus patterns in which the local spatial structure of 2-D images is changing due to motion in 3-D space and to stereoscopic projection. The strategy is to evaluate the visual acuity for spatial relations that are intrinsic to the geometric structure of the stimulus pattern versus those that are based on retinal positions. The optical stimulus patterns consist of points and line segments presented on cathode ray tube displays under computer control, with precise control of the spatial and temporal parameters of the patterns. Human observers discriminate patterns with slightly different geometric structures. Visual performance is measured by the psychometric function relating discrimination accuracy to the magnitude of a geometrical variable, providing separate measures of the gain and threshold for obtaining visual information about a particular geometrical variable.